LOW-COST AND RAPID PROTOTYPING IN AUTONOMOUS NAVIGATION BY USING MATLAB MOBILE AND SMARTPHONE SENSORS FOR A DRIVING ROBOT

Abstract

This paper explores the integration of MATLAB Mobile and smartphone sensor systems to develop and test autonomous driving robot control functions. With the ubiquity of mobile computing and embedded sensing, smartphones provide accessible inertial, vision, and localization data that can be leveraged for robotics. The research investigates methods of interfacing smartphone sensors with robot control via MATLAB, establishing real-time data acquisition, defining processing workflows, and implementing autonomous navigation strategies. Experimental results demonstrate that smartphone sensors, when fused via an Extended Kalman Filter (EKF) and processed on MATLAB Mobile, can support reliable perception and control loops for lane keeping and waypoint navigation, offering a cost-effective and rapid prototyping alternative to traditional LiDAR/DGPS setups.